1. Field of the Invention
The present invention relates generally to the field of processor-based imaging, and, more particularly, to a rapid and robust 3D/3D registration method.
2. Description of the Related Art
Registration of two volumetric data sets (i.e., a fixed volume and a moving volume) generally involves three steps: (1) computing a similarity measure and/or a difference measure quantifying a metric for comparing the volumes; (2) performing an optimization scheme, which searches through the parameter space (e.g., a six-dimensional rigid body motion) to maximize the similarity measure or to minimize the difference measure; and (3) performing a volume warping method, which applies the latest computed set of parameters to the moving volume to transform the moving volume closer the fixed volume.
In multi-modal volume registration, a key issue is involves choosing a well-behaved similarity measure that can robustly characterize a metric for the volumes. Additionally, the time for computing the similarity measure and applying the similarity measure to the moving volume is of substantial importance. Current methods for computing and applying a similarity measure suggest that, for a typical three-dimensional volume data sets, the computation time is in order of minutes. Most of this time is spent on computing the similarity measure over the whole volume set, and transforming (i.e., changing the coordinate frame) of the moving volume.
Some researchers have suggested random sampling of the volume data sets and performing computations only based on these random samples to decrease the computation load. Other researchers have proposed a hybrid technique, which selects a set of high-interest points (i.e., landmarks) within the volume and attempts to perform registration based on only the set of high-interest points. In both cases, a primary goal is to reduce the computational complexity of a full-blown volumetric matching by reducing the space in which the registration is performed, while preserving the accuracy and robustness as much as possible. For many practical applications, especially for interventional scenarios, the time used for performing a registration can be quite crucial.